In this paper, Fisher's linear discriminant is used for the binary classification problem for distinguishing between highly-cited papers and little-cited papers [1]}. The means \( \mu _{1} \)  and \( \mu _{2} \)  of each class for the training set are computed. Then, covariance matrices \(\Sigma _{1}\)  and \(\Sigma _{2}\)  for each class are calculated. The direction of the discriminating line is defined as:
\(\omega = (\Sigma _{1}+\Sigma _{2})^{-1}(\mu _{1}-\mu _{2}).\) 
